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Marcello Cirillo

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

9 papers
2 author rows

Possible papers

9

ICRA Conference 2015 Conference Paper

Efficient measurement planning for remote gas sensing with mobile robots

  • Muhammad Asif Arain
  • Marcello Cirillo
  • Victor Manuel Hernandez Bennetts
  • Erik Schaffernicht
  • Marco Trincavelli
  • Achim J. Lilienthal

The problem of gas detection is relevant to many real-world applications, such as leak detection in industrial settings and surveillance. In this paper we address the problem of gas detection in large areas with a mobile robotic platform equipped with a remote gas sensor. We propose a novel method based on convex relaxation for quickly finding an exploration plan that guarantees a complete coverage of the environment. Our method proves to be highly efficient in terms of computational requirements and to provide nearly-optimal solutions. We validate our approach both in simulation and in real environments, thus demonstrating its applicability to real-world problems.

ICRA Conference 2015 Conference Paper

Fast, continuous state path smoothing to improve navigation accuracy

  • Henrik Andreasson
  • Jari Saarinen
  • Marcello Cirillo
  • Todor Stoyanov
  • Achim J. Lilienthal

Autonomous navigation in real-world industrial environments is a challenging task in many respects. One of the key open challenges is fast planning and execution of trajectories to reach arbitrary target positions and orientations with high accuracy and precision, while taking into account non-holonomic vehicle constraints. In recent years, lattice-based motion planners have been successfully used to generate kinematically and kinodynamically feasible motions for non-holonomic vehicles. However, the discretized nature of these algorithms induces discontinuities in both state and control space of the obtained trajectories, resulting in a mismatch between the achieved and the target end pose of the vehicle. As endpose accuracy is critical for the successful loading and unloading of cargo in typical industrial applications, automatically planned paths have not be widely adopted in commercial AGV systems. The main contribution of this paper addresses this shortcoming by introducing a path smoothing approach, which builds on the output of a lattice-based motion planner to generate smooth drivable trajectories for non-holonomic industrial vehicles. In real world tests presented in this paper we demonstrate that the proposed approach is fast enough for online use (it computes trajectories faster than they can be driven) and highly accurate. In 100 repetitions we achieve mean end-point pose errors below 0. 01 meters in translation and 0. 002 radians in orientation. Even the maximum errors are very small: only 0. 02 meters in translation and 0. 008 radians in orientation.

IROS Conference 2014 Conference Paper

A lattice-based approach to multi-robot motion planning for non-holonomic vehicles

  • Marcello Cirillo
  • Tansel Uras
  • Sven Koenig

Coordinating fleets of autonomous, non-holonomic vehicles is paramount to many industrial applications. While there exists solutions to efficiently calculate trajectories for individual vehicles, an effective methodology to coordinate their motions and to avoid deadlocks is still missing. Decoupled approaches, where motions are calculated independently for each vehicle and then centrally coordinated for execution, have the means to identify deadlocks, but not to solve all of them. We present a novel approach that overcomes this limitation and that can be used to complement the deficiencies of decoupled solutions with centralized coordination. Here, we formally define an extension of the framework of lattice-based motion planning to multi-robot systems and we validate it experimentally. Our approach can jointly plan for multiple vehicles and it generates kinematically feasible and deadlock-free motions.

ICAPS Conference 2014 Conference Paper

Integrated Motion Planning and Coordination for Industrial Vehicles

  • Marcello Cirillo
  • Federico Pecora
  • Henrik Andreasson
  • Tansel Uras
  • Sven Koenig

A growing interest in the industrial sector for autonomous ground vehicles has prompted significant investment in fleet management systems. Such systems need to accommodate on-line externally imposed temporal and spatial requirements, and to adhere to them even in the presence of contingencies. Moreover, a fleet management system should ensure correctness, i. e. , refuse to commit to requirements that cannot be satisfied. We present an approach to obtain sets of alternative execution patterns (called trajectory envelopes) which provide these guarantees. The approach relies on a constraint-based representation shared among multiple solvers, each of which progressively refines trajectory envelopes following a least commitment principle.

ICAPS Conference 2013 Conference Paper

A Constraint-Based Approach for Proactive, Context-Aware Human Support

  • Federico Pecora
  • Marcello Cirillo
  • Francesca Dell'Osa
  • Jonas Ullberg
  • Alessandro Saffiotti

In this article we address the problem of realizing a service-providing reasoning infrastructure for pro-active humanassistance in intelligent environments. We propose SAM, an architecture which leverages temporal knowledge represented asrelations in Allen’s interval algebra and constraint-based temporal planning techniques. SAM provides two key capabilities forcontextualized service provision: human activity recognition and planning for controlling pervasive actuation devices. Whiledrawing inspiration from several state-of-the-art approaches, SAM provides a unique feature which has thus far not been addressed in the literature, namely the seamless integration of these two key capabilities. It does so by leveraging a constraint-basedreasoning paradigm whereby both requirements for recognition and for planning/execution are represented as constraints andreasoned upon continuously.

AAAI Conference 2013 Conference Paper

Simple Temporal Problems with Taboo Regions

  • T. K. Kumar
  • Marcello Cirillo
  • Sven Koenig

In this paper, we define and study the general framework of Simple Temporal Problems with Taboo regions (STPTs) and show how these problems capture metric temporal reasoning aspects which are common to many real-world applications. STPTs encode simple temporal constraints between events and user-defined taboo regions on the timeline, during which no event is allowed to take place. We discuss two different variants of STPTs. The first one deals with (instantaneous) events, while the second one allows for (durative) processes. We also provide polynomial-time algorithms for solving them. If all events or processes cannot be scheduled outside of the taboo regions, one needs to define and reason about “soft” STPTs. We show that even “soft” STPTs can be solved in polynomial time, using reductions to max-flow problems. The resulting algorithms allow for incremental computations, which is important for the successful application of our approach in realtime domains.

IROS Conference 2012 Conference Paper

On mission-dependent coordination of multiple vehicles under spatial and temporal constraints

  • Federico Pecora
  • Marcello Cirillo
  • Dimitar Dimitrov 0001

Coordinating multiple autonomous ground vehicles is paramount to many industrial applications. Vehicle trajectories must take into account temporal and spatial requirements, e. g. , usage of floor space and deadlines on task execution. In this paper we present an approach to obtain sets of alternative execution patterns (called trajectory envelopes) which satisfy these requirements and are conflict-free. The approach consists of multiple constraint solvers which progressively refine trajectory envelopes according to mission requirements. The approach leverages the notion of least commitment to obtain easily revisable trajectories for execution.

TIST Journal 2010 Journal Article

Human-aware task planning

  • Marcello Cirillo
  • Lars Karlsson
  • Alessandro Saffiotti

Consider a house cleaning robot planning its activities for the day. Assume that the robot expects the human inhabitant to first dress, then have breakfast, and finally go out. Then, it should plan not to clean the bedroom while the human is dressing, and to clean the kitchen after the human has had breakfast. In general, robots operating in inhabited environments, like households and future factory floors, should plan their behavior taking into account the actions that will be performed by the humans sharing the same environment. This would improve human-robot cohabitation, for example, by avoiding undesired situations for the human. Unfortunately, current task planners only consider the robot's actions and unexpected external events in the planning process, and cannot accommodate expectations about the actions of the humans. In this article, we present a human-aware planner able to address this problem. Our planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. Our planner has been tested both as a stand-alone component and within a full framework for human-robot interaction in a real environment.

ICAPS Conference 2009 Conference Paper

A Human-Aware Robot Task Planner

  • Marcello Cirillo
  • Lars Karlsson
  • Alessandro Saffiotti

The growing presence of household robots in inhabited environments arises the need for new robot task planning techniques. These techniques should take into consideration not only the actions that the robot can perform or unexpected external events, but also the actions performed by a human sharing the same environment, in order to improve the cohabitation of the two agents, e. g. , by avoiding undesired situations for the human. In this paper, we present a human-aware planner able to address this problem. This planner supports alternative hypotheses of the human plan, temporal duration for the actions of both the robot and the human, constraints on the interaction between robot and human, partial goal achievement and, most importantly, the possibility to use observations of human actions in the policy generated for the robot. The planner has been tested as a standalone component and in conjunction with our framework for human-robot interaction in a real environment.

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